Abstract

One of the key elements of the two major Air Traffic Management initiatives SESAR and NextGen is 4D-Trajectory-Based Operations. The main expected benefits are high predictability in advance, safety benefits, and improved efficiency. This paper covers the third issue: how can aircraft’s efficiency be improved?
Obvious techniques like flying more direct routes, applying efficient departure procedures and gliding down to the runway using the continuous descent approach procedure are already widely investigated. Furthermore, taking advantage of new 4D-based concepts, other constraining and therefore inefficient limitations can be questioned, e.g., flying according to semicircular rules, disrupting climbs and descents due to crossing traffic, holdings and path-stretching dissolving too dense traffic, or flying constant flight levels although aircraft get lighter due to burning fuel. In addition, improving weather forecast and measuring systems provide further potential. Tailwind conditions can be used beneficially to save some extra fuel; thunderstorms might be taken into account already in the planning phase.
Keeping in mind that each individual aircraft should be optimized to its own specific 4D trajectory, this isolated optimization would most certainly lead to conflicts. A global model of 4D airspace is necessary to ensure separation between all aircraft. Furthermore, each aircraft needs to separate from environmental constraints like thunderstorms and restricted areas.
In the last two years, DLR’s Institute of Flight Guidance investigated how to build a model of global 4D airspace and its included traffic. The resulting system allows handling huge traffic scenarios in a very efficient way. It features modelling of 4D-trajectories and 4D-envelopes covering both restricted areas (e.g. temporary military restricted areas and moving thunderstorms) and the aircraft’s trajectories. The underlying algorithm subdivides dense traffic areas in smaller 4D-spaces to identify potential conflicts. Used on a dense traffic scenario containing 10.000 aircraft (i.e. one day above Germany), the algorithm reaches an average of 25 milliseconds on an off-the-shelf PC hardware to check if a given trajectory produces conflicts with other trajectories or objects. For the whole scenario, the algorithm needs less than 5 minutes to produce a list of all conflicts while using acceptable 1,5 gigabyte of memory. Since deletion of an object from the airspace model nearly takes no time, the proposed model is predestined to do fast trial-and-error based conflict avoidance regarding all environmental constraints (surrounding traffic, meteo, restricted areas …) at the same time. The global 4D airspace model, the underlying subdivision algorithms and results based on above mentioned traffic scenario are described in more detail in the paper.